How to Create eCommerce Conversion Funnel in Tableau

How do you convert your site visitors into customers? If you have an eCommerce website having a high conversion rate is your top priority.

Depending on the size of your business and the kinds of products you offer, you have to create an easy journey for customers to complete a transaction. One way of improving it is by creating  an eCommerce conversion funnel dashboard.

Creating an eCommerce conversion funnel dashboard is your greatest tool to optimize user journey and maximize your sales.

In this guide, you’ll learn to create eCommerce conversion funnels in Tableau using Google analytics as data source. Plus, this guide will provide you tips on how to analyze and optimize user journey for higher conversion rate.

Why eCommerce conversion funnels is important?

At the end of the day you want leads, sales or conversions. By using visualization tools such as Tableau to create your conversion funnels, you are in the better position to see the problems your customers went through and how to fix them.

It will also provide you answers for the following questions.

    • Which pages have problems?
    • Which referring traffic has high intent or conversions?
    • Are we converting better in desktop compare to mobile?
    • How many visitors have left the site after reaching the payment step?



Creating your Tableau Conversion Funnel

In this guide we will use an extracted Google analytics data from Google sheets. One of the prerequisites before you begin is to ensure that Google Analytics captures your page URL accurately in Page report. This way, it will be easier to group your traffic according to each steps. Finally, I will use unique pageview as the main metric to quantify the traffic in the funnel.

  1. Import data from your source. In this example, I will use my dummy data from Google sheets (extracted from Google Analytics).

tableau conversion funnel configuration Google Sheets as data source

 

2.  I will also extract Date, Device Category and Traffic source as part of data extraction. I will use this variables later as I perform exploratory data analysis.

Please take note that customizing a measurement plan before sending data to Google Analytics is important. Doing this beforehand makes things much easier when creating your Bar Graphs. In this example, my eCommerce page URLs are already processed to each steps descriptive names. This means that instead of having URLs in the report, you will see the the names of each steps.

However, you can always use Custom Fields in Tableau to process your URLs into descriptive names.

dimensions and metrics in Tableau

create Calculated Field in Tableau

funnel analysis tableau using calculated metric field

 

3. After navigating to a sheet,  you will see the extracted Dimensions and Measures from the data source. Choose Unique Pageview from Measures and put it on Columns field.

funnel analysis tableau using unique page view metric on columns funnel analysis tableau using page views as metrics on the same column

4.  Navigate to Dimensions. Choose Page in the selection and put it on the Rows field.

tableau sales funnel using bar chart

5. Tableau will use a default chart. In this example Horizontal Bar Graph is the default chart. Right click on the Chart and chose Edit Axis.

tableau sales funnel analysis changing bar chart to reverse

6. Your Bar Graph will start to look like a funnel. Switch your canvas to Entire View to see the full window view of your Bar Graph.

visualized sales funnel tableau

fixing the width of the visualized sales funnel tableau

7. On the left side, you will see the Marks option, change the default visualization to Area in the list.

sales funnel tableau change visualization graph to area

8. You will now see the shape of the funnel. To provide more context on the Bar Graph, put the Unique Pageview metric on Labels. This is the quantity of unique page views that went through on each steps.

show tableau drop-off rate and conversion rate tableau

9. If you want to see the drop off percentage instead of the total unique page view per steps, right click on Labels and switch calculations to Percent Difference.

show tableau drop-off rate and conversion rate tableau 10. Now you can use the other variables as filters to start your data exploration. In this example, I applied Device Category and Medium to see the shape of my funnel depending on devices and referring traffic sources.

add filters for mobile devices in tableau funnel

The final output of the eCommerce conversion funnel should look like this.

add filters for traffic sources in tableau funnel

How to perform Tableau sales funnel  analysis to optimize user journey and get higher conversion rates?

You can use this dashboard to quantify the amount of traffic that leaves the site on each steps in the funnel. This exercise will give a clear idea on how to simplify steps that customers find very complicated or problematic.

Using variables as filters, it gives an idea about traffic sources that has brought high converting customers. This findings will help you decide on where to efficiently allocate your marketing budget.

The Mobile and Desktop filters gives you a glimpse about the customers experience on each devices. Since Desktop is more V shape in the first three steps compare to Mobile, you may want to consider eliminating steps or combining multiple steps on one screen in Mobile.

You can also define at which point a visitor becomes a lead. E.g., when they reach up to payment stage. Drop offs on payment stage can be used for  re-marketing using Display advertising or using EDM campaigns.

Quantitatively, you can use tools such as Hotjar to watch session recordings. You can use it to identify steps with huge drop offs. Session recordings gives you context on where the pain points are, whether navigation related or page errors.

Session recordings helps you understand what are the form fields they don’t want to fill out. By analyzing the recordings, you can decide what fields to remove that makes  a customer bounce off.

Hotjar also offers Heatmaps. This allows you to see the kind of interactions made on a specific steps and see whether CTAs (Call to Action) were not clicked or not noticed.

This exercise will help you identify steps on how to increase customer retention rates. It also allows you to discover where it is best to cross sell or up sell relevant products.

After evaluating your analysis, one of the actionable ways is to start running A/B testing and see any significant statistical results.

What are your conversion rate strategies?